公开(公告)号：US20240418886A1

公开(公告)日：2024-12-19

申请号：US18414336

申请日：2024-01-16

Applicant: Landmark Graphics Corporation

Inventor： Daniel Thomas-Possee ,  Satyan Singh ,  Graham Baines ,  Konstantin Osypov ,  Chaoshun Hu

IPC: G01V1/28

Abstract: A method for generating a merged survey dataset, that includes obtaining a plurality of survey datasets, calculating edges between survey datasets of the plurality of survey datasets, modifying the plurality of survey datasets, based on the edges, to obtain a plurality of modified survey datasets, and generating the merged survey dataset using the plurality of modified survey datasets.

公开(公告)号：US20240069237A1

公开(公告)日：2024-02-29

申请号：US18305601

申请日：2023-04-24

Applicant: Landmark Graphics Corporation

Inventor： Satyan Singh ,  Fan Jiang ,  Konstantin Osypov ,  Julianna Toms

IPC: G01V1/48 ,  G01V1/46

CPC classification number: G01V1/48 ,  G01V1/46

Abstract: A geoscience knowledge system can be obtained, where the geoscience knowledge system can include one or more of publicly available information, industry information, proprietary information, or task specific information. The geoscience knowledge system can be represented as a graph, graph data, network nodes, image data, tokenized data, or textualized data. Subsurface information can be obtained such as from seismic images or other types of sensor data. The subsurface information can be transformed or pre-processed, such as denoising, to make it suitable for use by the geoscience knowledge system. Then subsurface knowledge can be inferred from the subsurface information using the geoscience knowledge system. The subsurface knowledge can provided estimates, approximations, or value of the subterranean formation of interest in order to calculate an economic model parameter, such as a hydrocarbon distribution proximate the subterranean formation of interest.

公开(公告)号：US20250052918A1

公开(公告)日：2025-02-13

申请号：US18233054

申请日：2023-08-11

Applicant: Landmark Graphics Corporation

Inventor： Satyan Singh ,  Konstantin Osypov ,  Graham Baines

IPC: G01V1/04 ,  G01V1/38

Abstract: A method for creating a generated signal which includes training a signal generator using a physics informed constraint, providing, to the signal generator, raw data that includes a signal and noise, where the signal generator processes the raw data to create the generated signal, and obtaining the generated signal from the signal generator.

公开(公告)号：US20240069228A1

公开(公告)日：2024-02-29

申请号：US17896748

申请日：2022-08-26

Applicant: Landmark Graphics Corporation

Inventor： Konstantin Osypov ,  Fan Jiang ,  Marcelo Gomes ,  Satyan Singh

IPC: G01V1/30 ,  E21B49/00 ,  G01V1/34

CPC classification number: G01V1/30 ,  E21B49/00 ,  G01V1/345 ,  G01V2210/60 ,  G01V2210/74

Abstract: The disclosure relates to determining rock properties of subterranean formations and learning the distribution of hydrocarbons in the formations. A geometrical element spread function is disclosed that quantifies distortion of the geology as seen by the geophysicists who process seismic images of the subterranean formations. A method of determining the rock properties using the seismic images and synthetic images is provided. In one example, the method includes: (1) obtaining seismic data from a subterranean formation using a seismic acquisition system, (2) generating one or more seismic images of the subterranean formation using the seismic data, (3) creating one or more synthetic images from the one or more seismic images, and (4) determining rock properties of the subterranean formation based on the one or more seismic images and the one or more synthetic images.

公开(公告)号：US20230152480A1

公开(公告)日：2023-05-18

申请号：US17527245

申请日：2021-11-16

Applicant: Landmark Graphics Corporation

Inventor： Satyan Singh ,  Philip Norlund ,  Adrian Sanchez Rodriguez ,  Eugene Wolfe ,  Steven Angelovich

IPC: G01V1/36 ,  G01V1/28

CPC classification number: G01V1/364 ,  G01V1/282 ,  G01V2210/324

Abstract: System and methods of random noise attenuation are provided. A first model may be trained to extract random noise from seismic datasets. A second model may be trained to reconstruct leaked signals from the random noise extracted by the first model. A seismic dataset corresponding to a subsurface reservoir formation and including random noise may be obtained. Using the trained first model, at least a portion of the random noise may be extracted from the first seismic dataset. Using the trained second model, a leaked signal, which includes a portion of the seismic dataset, may be reconstructed from the extracted random noise. A cleaned seismic dataset is generated based on the reconstructed leaked signal and the extracted random noise. The cleaned seismic dataset may include a quantity of random noise that is less than that of the original seismic dataset.